67165

Автор(ы): 

Автор(ов): 

2

Параметры публикации

Тип публикации: 

Доклад

Название: 

Algorithms for Informative Features Extraction in the Problem of Data Mining on Item Related State Evaluation

DOI: 

10.1109/MLSD52249.2021.9600186

Наименование конференции: 

  • 2021 14th International Conference "Management of Large-Scale System Development" (MLSD)

Наименование источника: 

  • Proceedings of the 14th International Conference "Management of Large-Scale System Development" (MLSD)

Город: 

  • Moscow

Издательство: 

  • IEEE

Год издания: 

2021

Страницы: 

https://ieeexplore.ieee.org/document/9600186
Аннотация
The algorithms for informative features extraction in the task of data mining on item related state evaluation have been considered in the report by way of example of evaluating and forecasting the technical status (early diagnosis task) of unmanned aerial vehicle electric motor where the reporting set of controlled variable values is applicable to a certain class or hazard level.

Библиографическая ссылка: 

Голев А.В., Огородников О.В. Algorithms for Informative Features Extraction in the Problem of Data Mining on Item Related State Evaluation / Proceedings of the 14th International Conference "Management of Large-Scale System Development" (MLSD). Moscow: IEEE, 2021. С. https://ieeexplore.ieee.org/document/9600186.